An automatic calibration approach using a hierarchy of 3 techniques (screening, parameterization of physically immeasurable parameters, & parameter sensitivity analysis) was performed at the parameter identification stage. The sensitivity analysis was conducted using a stepwise regression approach for 35 different input parameters. Application of the 3 techniques reduced the calibrable parameters to 20: 12 for streamflow & 8 for sediment. Latin hypercube sampling was used to generate input data frm assigned disributions and ranges, and parameter estimation was performed using a genetic algorithm. A GLUE method was used to evaluate uncertaintity. The authors state that the poor verification results may be due in part to the relatively short period used for calibration.